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DBMS > Axibase vs. Datomic vs. FatDB vs. Google Cloud Datastore vs. Warp 10

System Properties Comparison Axibase vs. Datomic vs. FatDB vs. Google Cloud Datastore vs. Warp 10

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonDatomic  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonWarp 10  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSRelational DBMSDocument store
Key-value store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#288  Overall
#25  Time Series DBMS
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.datomic.comcloud.google.com/­datastorewww.warp10.io
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docswww.warp10.io/­content/­02_Getting_started
DeveloperAxibase CorporationCognitectFatCloudGoogleSenX
Initial release20132012201220082015
Current release155851.0.6735, June 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infolimited edition freecommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureC#Java
Server operating systemsLinuxAll OS with a Java VMWindowshostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyesyes, details hereyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLSQL-like query languagenono infoVia inetgration in SQL ServerSQL-like query language (GQL)no
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
RESTful HTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Jupyter
WebSocket
Supported programming languagesGo
Java
PHP
Python
R
Ruby
Clojure
Java
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsyes infovia applicationsusing Google App Engineyes infoWarpScript
TriggersyesBy using transaction functionsyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersselectable replication factorMulti-source replication using Paxosselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
AxibaseDatomicFatDBGoogle Cloud DatastoreWarp 10
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